SynthesisGenome biology2018
Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis.
Synthesis in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.
- Population structure discovery in meta-analyzed microbial communities and inflammatory bowel disease using MMUPHin.Genome biology · 2022Pooled it
- Distant Metastasis in Colorectal Cancer Patients-Do We Have New Predicting Clinicopathological and Molecular Biomarkers? A Comprehensive Review.International journal of molecular sciences · 2020Pooled it
- Genetic differences between primary colorectal cancer and its paired synchronous and metachronous metastases.International journal of cancer · 2026Article
- Novel nested conformal prediction analysis to unravel complexity in patient subtyping.Frontiers in artificial intelligence · 2026Article
- Quantifying Metagenomic Strain Associations from Microbiomes with Anpan.bioRxiv : the preprint server for biology · 2025Article
- The Cancer Spectrum Theory.Cancer discovery · 2024Article
- Construction of an immune predictive model and identification of TRIP6 as a prognostic marker and therapeutic target of CRC by integration of single-cell and bulk RNA-seq data.Cancer immunology, immunotherapy : CII · 2024Article
- glmmPen: High Dimensional Penalized Generalized Linear Mixed Models.The R journal · 2023Article
- Multi-label transcriptional classification of colorectal cancer reflects tumor cell population heterogeneity.Genome medicine · 2023Article
- GenomicSuperSignature facilitates interpretation of RNA-seq experiments through robust, efficient comparison to public databases.Nature communications · 2022Article
- Refining colorectal cancer classification and clinical stratification through a single-cell atlas.Genome biology · 2022Article
- Global colorectal cancer burden in 2020 and projections to 2040.Translational oncology · 2021Review
- Metastatic heterogeneity of the consensus molecular subtypes of colorectal cancer.NPJ genomic medicine · 2021Article
- Meta-Analysis of Microdissected Breast Tumors Reveals Genes Regulated in the Stroma but Hidden in Bulk Analysis.Cancers · 2021Article
- Oncogenic Features in Histologically Normal Mucosa: Novel Insights Into Field Effect From a Mega-Analysis of Colorectal Transcriptomes.Clinical and translational gastroenterology · 2020Article
- Genomic heterogeneity in bladder cancer: challenges and possible solutions to improve outcomes.Nature reviews. Urology · 2020Review
- Comprehensive transcriptome profiling of Taiwanese colorectal cancer implicates an ethnic basis for pathogenesis.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
19 authors at 7 institutions in 1 country.
Funding
Abstract
backgroundPrevious approaches to defining subtypes of colorectal carcinoma (CRC) and other cancers based on transcriptomes have assumed the existence of discrete subtypes. We analyze gene expression patterns of colorectal tumors from a large number of patients to test this assumption and propose an approach to identify potentially a continuum of subtypes that are present across independent studies and cohorts.
resultsWe examine the assumption of discrete CRC subtypes by integrating 18 published gene expression datasets and > 3700 patients, and contrary to previous reports, find no evidence to support the existence of discrete transcriptional subtypes. Using a meta-analysis approach to identify co-expression patterns present in multiple datasets, we identify and define robust, continuously varying subtype scores to represent CRC transcriptomes. The subtype scores are consistent with established subtypes (including microsatellite instability and previously proposed discrete transcriptome subtypes), but better represent overall transcriptional activity than do discrete subtypes. The scores are also better predictors of tumor location, stage, grade, and times of disease-free survival than discrete subtypes. Gene set enrichment analysis reveals that the subtype scores characterize T-cell function, inflammation response, and cyclin-dependent kinase regulation of DNA replication.
conclusionsWe find no evidence to support discrete subtypes of the CRC transcriptome and instead propose two validated scores to better characterize a continuity of CRC transcriptomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.